Search Results

Vehicle restraint system design is a difficult optimization problem to solve because (1) the nature of the problem is highly nonlinear, non-convex, noisy, and discontinuous; (2) there are large numbers of discrete and continuous design variables; (3) a design has to meet safety performance requirements for multiple crash modes simultaneously, hence there are a large number of design constraints. Based on the above knowledge of the problem, it is understandable why design of experiment (DOE) does not produce a high-percentage of feasible solutions, and it is difficult for response surface methods (RSM) to capture the true landscape of the problem. Furthermore, in order to keep the restraint system more robust, the complexity of restraint system content needs to be minimized in addition to minimizing the relative risk score to achieve New Car Assessment Program (NCAP) 5-star rating.

Understanding reliability is critical in design, maintenance and durability analysis of engineering systems. A reliability simulation methodology is presented in this paper for vehicle fleets using limited data. The method can be used to estimate the reliability of non-repairable as well as repairable systems. It can optimally allocate, based on a target system reliability, individual component reliabilities using a multi-objective optimization algorithm. The algorithm establishes a Pareto front that can be used for optimal tradeoff between reliability and the associated cost. The method uses Monte Carlo simulation to estimate the system failure rate and reliability as a function of time. The probability density functions (PDF) of the time between failures for all components of the system are estimated using either limited data or a user-supplied MTBF (mean time between failures) and its coefficient of variation.

Embedded systems continue to become more complex. As a result, more companies are utilizing model-based design (MBD) development methods and tools. The use of MBD methods and tools is helpful in increasing time to market and having instant feedback on the system design. One area that continues to mature is the testing and verification of the MBD systems. This paper introduces a hybrid approach to functional tests. The test system is composed of simulation software and real-time hardware. It is not always necessary to test a system in a real-time environment, but it is recommended if the goal is to deploy the system to a situation that requires real-time response. Vehicle drive cycles and powertrain control are utilized in this research as the example test case for this paper. In order to test the algorithms on a real-time system, it is necessary to understand the target controller's computing limitations and adjust the algorithms to meet these limitations.

Styrene-Butadiene Rubber (SBR), a copolymer of butadiene and styrene, is widely used in the automotive industry due to its high durability and resistance to abrasion, oils and oxidation. Some of the common applications include tires, vibration isolators, and gaskets, among others. This paper characterizes the dynamic behavior of SBR and discusses the suitability of a visco-elastic model of elastomers, known as the Kelvin model, from a mathematical and physical point of view. An optimization algorithm is used to estimate the parameters of the Kelvin model. The resulting model was shown to produce reasonable approximations of measured dynamic stiffness. The model was also used to calculate the self heating of the elastomer due to energy dissipation by the viscous damping components in the model. Developing such a predictive capability is essential in understanding the dynamic behavior of elastomers considering that their dynamic stiffness can in general depend on temperature.

Frames are important structures found in many transportation applications such as automotive bodies and train cars. They are also widely employed in buildings, bridges, and other load bearing designs. When a frame is carrying multiple loads, it can potentially risk a catastrophic buckling failure. The loads on the frame may be non-proportional in that one force stays constant while the other is increased until buckling occurs. In this study the buckling problem is formulated as a constrained eigenvalue problem (CEVP). As opposed to other CEVP in which the eigenvectors are forced to comply with a number of the constraints, the eigenvalues in the current CEVP are subject to some equality constraints. A numerical algorithm for solving the constrained eigenvalue problem is presented. The algorithm is a simple trapping scheme in which the computation starts with an initial guess and a window containing the potential target for the eigenvalue is identified.

A detailed description of the oxidative stability of GM's DEXRON®-VI Factory Fill Automatic Transmission Fluid (ATF) is provided, which can be integrated into a working algorithm to estimate the end of useful oxidative life of the fluid. As described previously, an algorithm to determine the end of useful life of an automatic transmission fluid exists and is composed of two simultaneous counters, one monitoring bulk oxidation and the other monitoring friction degradation [1]. When either the bulk oxidation model or the friction model reach the specified limit, a signal can be triggered to alert the driver that an ATF change is required. The data presented in this report can be used to develop the bulk oxidation model. The bulk oxidation model is built from a large series of bench oxidation tests. These data can also be used independent of a vehicle to show the relative oxidation resistance of this fluid, at various temperatures, compared to other common lubricants.

Response Surface Model (RSM)-based optimization is widely used in engineering design. The major strength of RSM-based optimization is its short computational time. The expensive real simulation models are replaced with fast surrogate models. However, this method may have some difficulties to reach the full potential due to the errors between RSM and the real simulations. RSM's accuracy is limited by the insufficient number of Design of Experiments (DOE) points and the inherent randomness of DOE. With recent developments in advanced optimization algorithms and High Performance Computing (HPC) capability, Direct Multidisciplinary Design Optimization (DMDO) receives more attention as a promising future optimization strategy. Advanced optimization algorithm reduces the number of function evaluations, and HPC cut down the computational turnaround time of function evaluations through fully utilizing parallel computation.

Sheet metal forming of automobile body panel consists of two processes performed in series: binder forming and punch forming. Due to differences in deformation characteristics of the two forming processes, their analysis methods are different. The binder wrap surface shape and formed part shape are calculated using different mathematical models and different finite element codes, e.g., WRAPFORM and PANELFORM, respectively. The output of the binder forming analysis may not be directly applicable to the subsequent punch forming analysis. Interpolation, or approximation, of the calculated binder wrap surface geometry is needed. This surface representation requirement is carried out using computer aided geometric design tools. This paper discusses the use of such a tool, SURFPLAN, to link WRAPFORM and PANELFORM calculations.

This paper describes a numerical simulation technique applicable to the FMVSS 214 side impact test through the use of the finite element method (FEM) technology. The paper outlines the development of the side impact dummy (SID), moving deformable barrier (MDB) and the test vehicle FEM models, as well as the development of new advanced constitutive models of materials and algorithms in LS-DYNA3D which are related to the topic. Presented in the paper are some initial simulation problems which were encountered and solved, as well as the correlation of the simulation data to the physical test.

Side impact dummy (SID) is a human-like test device used in the National Highway Transportation Safety Administration (NHTSA) mandated side impact test of vehicles sold in the USA. A finite element model of SID has been developed at GM as a part of a project to simulate the side impact test. The objective is to better predict physical test results by replacing traditional rigid-body lumped parameter models with a finite element model. The project included, besides mesh generation, the development of new LS-DYNA3D constitutive models for rubber and foam-like materials, and enhancements of contact interface and other algorithms. This paper describes the GM SID finite element model and its performance in side impact test simulations.

Growing concerns about the environment, energy dependency, and unstable fuel prices have increased the market share of electric vehicles. This has led to an increased demand for energy efficient routing algorithms that are optimized for electric vehicles. Traditional routing algorithms are focused on finding the shortest distance or the least time route between two points. These approaches have been working well for fossil fueled vehicles. Electric vehicles, on the other hand, require different route optimization techniques. Negative edge costs, battery power and capacity limits, as well as vehicle parameters that are only available at query time, make the task of electric vehicle routing a challenging problem. In this paper, we present a simulated solution to the energy efficient routing for electric vehicles using Particle Swarm Optimization. Simulation results show improvements in the energy consumption of the electric vehicle when applied to a start-to-destination routing problem.

A self-calibrating phase-shifting technique using a Michelson Interferometer is presented to measure phase distribution more accurately in Digital Speckle Pattern Interferometry (DSPI). DSPI is a well-established technique for the determination of whole field deformation via quantitatively measuring the phase distribution of speckle interferograms that use the phase shifting technique. In the phase shifting technique, the phase distribution in a speckle interferogram is quantitatively determined by recording multiple intensity images (usually four images) in which a constant phase shift, e.g. 90 degrees, is introduced between each consecutive image. A precise phase determination is greatly dependent on the accuracy of the phase shift introduced. The popular methods to minimize the error resulting from inaccurate phase shift use various algorithms and need to record five or eight images (rather than four images).